Mesenchymal stem cells in experimental autoimmune encephalomyelitis model of multiple sclerosis: A systematic review and meta-analysis.

BACKGROUND/AIMS: Mesenchymal stem cells (MSCs) transplantation has been considered a possible therapeutic method for Multiple Sclerosis (MS). However, no quantitative data synthesis of MSCs therapy for MS exists. We conducted a systematic review and meta-analysis to evaluate the effects of MSCs in experimental autoimmune encephalomyelitis (EAE) animal model of MS. METHODS: We identified eligible studies published from January 1980 to January 2017 by searching four electronic databases (PubMed, MEDLINE, Embase and Web of Science). The outcome was the effects of MSCs on clinical performance evaluated by the EAE clinical score. RESULTS: 36 preclinical studies including 675 animals in MSCs treatment group, and 693 animals in control group were included in this meta-analysis. We found that MSCs transplantation significantly ameliorated the symptoms and delayed the disease progression (SMD = -1.25, 95% CI: -1.45 to -1.05, P < 0.001). However, no significant differences in effect sizes were unveiled relative to clinical score standard (P = 0.35), type of MSCs (P = 0.35), source of MSCs (P = 0.06), MSCs dose (P = 0.44), delivery methods (P = 0.31) and follow up period (P = 0.73). CONCLUSIONS: The current study showed that MSCs transplantation could ameliorate clinical performance in EAE animal model of MS. These findings support the further studies translate MSCs to treat MS in humans.

A study of feature extraction for Alzheimer's disease based on resting-state fMRI.

The Alzheimer's Disease (AD) has become a major threat of human health with its incidence rate ascending year by year. Early diagnosis of AD is very important for AD patients to keep life quality. The resting-state fMRI (rs-fMRI) which precisely reflects the brain changes on the resting state of individuals provides a quantitative approach, which has been introduced to distinguish AD patients from normal population. In this study, we proposed a method to find the most distinctive features identifying AD patients from rs-fMRI images. The ALFF and ReHo parameters based on pre-processed rs-fMRI data were extracted, and some key parameters of the brain functional network based on graph theory were calculated. Then we tested the recognition performance of different classifiers, and the best classification algorithm, that is, Support Vector Machine (SVM) with linear-kernel are selected. Finally through a recursive feature selection procedure, we got the most distinctive feature set. Additionally, this study also implies that there may be several changes in some particular ROIs of the brain during the AD development.

P450 enzyme-inducing and non-enzyme-inducing antiepileptic drugs for seizure prophylaxis after glioma resection surgery: a meta-analysis.

PURPOSE: The prognoses of seizure treatment with P450 enzyme-inducing and non-enzyme-inducing antiepileptic drugs after glioma resection surgery were investigated across several clinical studies. However, the results of these studies are inconsistent. We examined the relevant studies and conducted a meta-analysis of these two types of anti-epileptic drugs. METHODS: A bibliography search using the EMBASE, MEDLINE, ClinicalTrials.gov, and Cochrane Central Register of Controlled Trials databases was performed to identify potentially relevant articles and conference abstracts that investigated the effects of non-enzyme-inducing antiepileptic drugs (NEIAEDs) and enzyme-inducing antiepileptic drugs (EIAEDs) on the seizure prognoses of glioma patients. RESULTS: One RCT study and five observational studies were included. Pooled estimates of the relative risks (OR) and 95% confidence intervals (CI) were calculated. The pooled odds ratio for NEIAEDs vs. EIAEDs for patients with glioma was 1.12 (95% CI=0.70-2.10). The pooled odds ratio for NEIAEDs vs. EIAEDs for low-grade gliomas was 1.77 (95% CI=0.71-4.40). The pooled odds ratio for LEV vs. PHY was 1.459 (95% CI=0.731-2.910). CONCLUSIONS: No significant difference between the efficacies of P450 enzyme-inducing and non-enzyme-inducing antiepileptic drugs for prophylactic late seizure treatment was observed. However, few RCTs were available, and the acquisition of further evidence through high-quality RCTs is highly recommended.

Ki-67 overexpression in WHO grade II gliomas is associated with poor postoperative seizure control.

PURPOSE: Seizures are the most common initial symptom in patients with low-grade gliomas, and approximately 30% of these patients still suffer from epilepsy after gross-total resection of the tumour. We examined the relationship between the overexpression of ki-67 in WHO grade II gliomas and seizure control. METHODS: A series of 93 histologically confirmed WHO grade II glioma tissues were analysed through immunohistochemical staining for ki-67 expression. Follow-up visits regarding seizure control were scheduled at 12 months. The Engel classification was used to categorise patients' seizure status. RESULTS: Of the 93 patients analysed, 65 (66.3%) patients initially presented with seizures. A total of 36 patients were diagnosed with WHO grade II oligodendrogliomas, 29 patients had oligoastrocytomas and 28 patients had astrocytomas. Ki-67 was over-expressed in 15 patients. One year after surgery poor seizure control was observed in 11 of these patients. In contrast, low ki-67 expression (<10%) was found in 78 patients. Poor seizure control was observed in 36 patients (difference between ki-67 over- and low expression groups P = 0.002). Logistic regression analysis revealed that patients with gross-total resection achieved better seizure control while ki-67 overexpression and age below 38 years were poor seizure control factors explained of the variance of seizure outcome (OR: 0.382, 4.354 and 1.822, respectively). CONCLUSIONS: In WHO grade II gliomas, Ki-67 is a molecular marker which predicts poor seizure control of glioma patients after the resection of the tumour. Gross-total resection, ki-67 overexpression and age below 38 years significantly affect seizure prognosis.